Practical Bioinformatics For Beginners From Raw Sequence Analysis To Machine Learning Applications

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Practical Bioinformatics For Beginners: From Raw Sequence Analysis To Machine Learning Applications

Lloyd Wai Yee Low,Martti Tapani Tammi
Practical Bioinformatics For Beginners From Raw Sequence Analysis To Machine Learning Applications Book PDF

Author : Lloyd Wai Yee Low,Martti Tapani Tammi
Publisher : World Scientific
Page : 268 pages
File Size : 52,8 Mb
Release : 2023-01-17
Category : Science
ISBN : 9789811259005

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Practical Bioinformatics For Beginners: From Raw Sequence Analysis To Machine Learning Applications by Lloyd Wai Yee Low,Martti Tapani Tammi Pdf

Next-Generation Sequencing (NGS) is increasingly common and has applications in various fields such as clinical diagnosis, animal and plant breeding, and conservation of species. This incredible tool has become cost-effective. However, it generates a deluge of sequence data that requires efficient analysis. The highly sought-after skills in computational and statistical analyses include machine learning and, are essential for successful research within a wide range of specializations, such as identifying causes of cancer, vaccine design, new antibiotics, drug development, personalized medicine, and increased crop yields in agriculture.This invaluable book provides step-by-step guides to complex topics that make it easy for readers to perform specific analyses, from raw sequenced data to answer important biological questions using machine learning methods. It is an excellent hands-on material for lecturers who conduct courses in bioinformatics and as reference material for professionals. The chapters are standalone recipes making them suitable for readers who wish to self-learn selected topics. Readers gain the essential skills necessary to work on sequenced data from NGS platforms; hence, making themselves more attractive to employers who need skilled bioinformaticians.

Bioinformatics

Hamid D. Ismail
Bioinformatics Book PDF

Author : Hamid D. Ismail
Publisher : CRC Press
Page : 383 pages
File Size : 47,9 Mb
Release : 2023-06-29
Category : Computers
ISBN : 9781000861709

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Bioinformatics by Hamid D. Ismail Pdf

This book contains the latest material in the subject, covering next generation sequencing (NGS) applications and meeting the requirements of a complete semester course. This book digs deep into analysis, providing both concept and practice to satisfy the exact need of researchers seeking to understand and use NGS data reprocessing, genome assembly, variant discovery, gene profiling, epigenetics, and metagenomics. The book does not introduce the analysis pipelines in a black box, but with detailed analysis steps to provide readers with the scientific and technical backgrounds required to enable them to conduct analysis with confidence and understanding. The book is primarily designed as a companion for researchers and graduate students using sequencing data analysis but will also serve as a textbook for teachers and students in biology and bioscience.

Bioinformatics, second edition

Pierre Baldi,Søren Brunak
Bioinformatics second edition Book PDF

Author : Pierre Baldi,Søren Brunak
Publisher : MIT Press
Page : 492 pages
File Size : 43,8 Mb
Release : 2001-07-20
Category : Computers
ISBN : 026202506X

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Bioinformatics, second edition by Pierre Baldi,Søren Brunak Pdf

A guide to machine learning approaches and their application to the analysis of biological data. An unprecedented wealth of data is being generated by genome sequencing projects and other experimental efforts to determine the structure and function of biological molecules. The demands and opportunities for interpreting these data are expanding rapidly. Bioinformatics is the development and application of computer methods for management, analysis, interpretation, and prediction, as well as for the design of experiments. Machine learning approaches (e.g., neural networks, hidden Markov models, and belief networks) are ideally suited for areas where there is a lot of data but little theory, which is the situation in molecular biology. The goal in machine learning is to extract useful information from a body of data by building good probabilistic models—and to automate the process as much as possible. In this book Pierre Baldi and Søren Brunak present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. The book is aimed both at biologists and biochemists who need to understand new data-driven algorithms and at those with a primary background in physics, mathematics, statistics, or computer science who need to know more about applications in molecular biology. This new second edition contains expanded coverage of probabilistic graphical models and of the applications of neural networks, as well as a new chapter on microarrays and gene expression. The entire text has been extensively revised.

Bioinformatics

Rob Botwright
Bioinformatics Book PDF

Author : Rob Botwright
Publisher : Unknown
Page : 0 pages
File Size : 40,8 Mb
Release : 2024-02-15
Category : Computers
ISBN : 1839386894

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Bioinformatics by Rob Botwright Pdf

Introducing the Ultimate Bioinformatics Book Bundle! Dive into the world of bioinformatics with our comprehensive book bundle, featuring four essential volumes that cover everything from foundational concepts to advanced applications. Whether you're a student, researcher, or practitioner in the life sciences, this bundle has something for everyone. Book 1: Bioinformatics Basics Get started with the basics of bioinformatics in this introductory volume. Learn about algorithms, concepts, and principles that form the backbone of bioinformatics research. From sequence analysis to genetic variation, this book lays the groundwork for understanding the fundamental aspects of bioinformatics. Book 2: Coding in Bioinformatics Take your skills to the next level with our coding-focused volume. Explore scripting languages like Python and R, and discover how to apply them to bioinformatics tasks. From data manipulation to machine learning, this book covers a wide range of coding techniques and applications in bioinformatics. Book 3: Exploring Data Science in Bioinformatics Delve into the world of data science and its applications in bioinformatics. Learn about exploratory data analysis, statistical inference, and machine learning techniques tailored specifically for biological data. With practical examples and case studies, this book helps you extract meaningful insights from complex datasets. Book 4: Mastering Biostatistics in Bioinformatics Unlock the power of biostatistics with our advanced methods volume. Explore cutting-edge statistical techniques for analyzing biological data, including survival analysis, meta-analysis, and more. Whether you're conducting experimental studies or analyzing clinical data, this book equips you with the tools you need to draw meaningful conclusions. Why Choose Our Bundle? - Comprehensive Coverage: Covering everything from basic concepts to advanced methods, this bundle provides a complete overview of bioinformatics. - Practical Focus: With hands-on coding exercises and real-world examples, our books emphasize practical skills and applications. - Expert Authors: Authored by experts in the field of bioinformatics, each book offers valuable insights and expertise. - Versatile Learning: Whether you're a beginner or an experienced practitioner, our bundle caters to learners of all levels. Don't miss out on this opportunity to enhance your skills and knowledge in bioinformatics. Order your copy of the Bioinformatics Book Bundle today!

The Practical Bioinformatician

Limsoon Wong
The Practical Bioinformatician Book PDF

Author : Limsoon Wong
Publisher : World Scientific
Page : 539 pages
File Size : 55,7 Mb
Release : 2004
Category : Medical
ISBN : 9789812388469

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The Practical Bioinformatician by Limsoon Wong Pdf

Computer scientists have increasingly been enlisted as "bioinformaticians" to assist molecular biologists in their research. This book is a practical introduction to bioinformatics for these computer scientists. The chapters are in-depth discussions by expert bioinformaticians on both general techniques and specific approaches to a range of selected bioinformatics problems. The book is organized into clusters of chapters on the following topics: - Overview of modern molecular biology and a broad spectrum of techniques from computer science -- data mining, machine learning, mathematical modeling, sequence alignment, data integration, workflow development, etc. - In-depth discussion of computational recognition of functional and regulatory sites in DNA sequences. - Incisive discussion of computational prediction of secondary structure of RNA sequences. - Overview of computational prediction of protein cellular localization, and selected discussions of inference of protein function. - Overview of methods for discovering protein-protein interactions. - Detailed discussion of approaches to gene expression analysis for the diagnosis of diseases, the treatment of diseases, and the understanding of gene functions. - Case studies on analysis of phylogenies, functional annotation of proteins, construction of purposebuilt integrated biological databases, and development of workflows underlying the large-scale-effort gene discovery. - Written in a practical, in-depth tutorial style - Covers a broad range of bioinformatics topics and of techniques used in bioinformatics - Comprehensive overviews of the development of various approaches in a number of selectedtopics - In-depth exposition of a number of important topics - Contributions by prominent researchers: Vladimir Bajic, Ming Li, Kenta Nakai, Limsoon Wong, Cathy Wu, etc. - Extensive, integrated references to background liter

Artificial Intelligence in Bioinformatics

Mario Cannataro,Pietro Hiram Guzzi,Giuseppe Agapito,Chiara Zucco,Marianna Milano
Artificial Intelligence in Bioinformatics Book PDF

Author : Mario Cannataro,Pietro Hiram Guzzi,Giuseppe Agapito,Chiara Zucco,Marianna Milano
Publisher : Elsevier
Page : 270 pages
File Size : 49,6 Mb
Release : 2022-05-12
Category : Computers
ISBN : 9780128229293

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Artificial Intelligence in Bioinformatics by Mario Cannataro,Pietro Hiram Guzzi,Giuseppe Agapito,Chiara Zucco,Marianna Milano Pdf

Artificial Intelligence in Bioinformatics: From Omics Analysis to Deep Learning and Network Mining reviews the main applications of the topic, from omics analysis to deep learning and network mining. The book includes a rigorous introduction on bioinformatics, also reviewing how methods are incorporated in tasks and processes. In addition, it presents methods and theory, including content for emergent fields such as Sentiment Analysis and Network Alignment. Other sections survey how Artificial Intelligence is exploited in bioinformatics applications, including sequence analysis, structure analysis, functional analysis, protein classification, omics analysis, biomarker discovery, integrative bioinformatics, protein interaction analysis, metabolic networks analysis, and much more. Bridges the gap between computer science and bioinformatics, combining an introduction to Artificial Intelligence methods with a systematic review of its applications in the life sciences Brings readers up-to-speed on current trends and methods in a dynamic and growing field Provides academic teachers with a complete resource, covering fundamental concepts as well as applications

Practical Bioinformatics

Janusz M. Bujnicki
Practical Bioinformatics Book PDF

Author : Janusz M. Bujnicki
Publisher : Springer Science & Business Media
Page : 292 pages
File Size : 53,8 Mb
Release : 2004-03-03
Category : Computers
ISBN : 3540206132

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Practical Bioinformatics by Janusz M. Bujnicki Pdf

Bridges the gap between bioinformaticists and molecular biologists, i.e. the developers and the users of computational methods for biological data analysis and in that it presents examples of practical applications of the bioinformatics tools in the "daily practice" of an experimental research scientist.

Bioinformatics: A Practical Handbook Of Next Generation Sequencing And Its Applications

Low Lloyd Wai Yee,Tammi Martti Tapani
Bioinformatics A Practical Handbook Of Next Generation Sequencing And Its Applications Book PDF

Author : Low Lloyd Wai Yee,Tammi Martti Tapani
Publisher : #N/A
Page : 252 pages
File Size : 49,9 Mb
Release : 2017-07-26
Category : Computers
ISBN : 9789813144767

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Bioinformatics: A Practical Handbook Of Next Generation Sequencing And Its Applications by Low Lloyd Wai Yee,Tammi Martti Tapani Pdf

Rapid technological developments have led to increasingly efficient sequencing approaches. Next Generation Sequencing (NGS) is increasingly common and has become cost-effective, generating an explosion of sequenced data that need to be analyzed. The skills required to apply computational analysis to target research on a wide range of applications that include identifying causes of cancer, vaccine design, new antibiotics, drug development, personalized medicine and higher crop yields in agriculture are highly sought after. This invaluable book provides step-by-step guides to complex topics that make it easy for readers to perform essential analyses from raw sequenced data to answering important biological questions. It is an excellent hands-on material for teachers who conduct courses in bioinformatics and as a reference material for professionals. The chapters are written to be standalone recipes making it suitable for readers who wish to self-learn selected topics. Readers will gain skills necessary to work on sequenced data from NGS platforms and hence making themselves more attractive to employers who need skilled bioinformaticians to handle the deluge of data.

R Bioinformatics Cookbook

Dan MacLean
R Bioinformatics Cookbook Book PDF

Author : Dan MacLean
Publisher : Packt Publishing Ltd
Page : 307 pages
File Size : 55,7 Mb
Release : 2019-10-11
Category : Science
ISBN : 9781789955590

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R Bioinformatics Cookbook by Dan MacLean Pdf

Over 60 recipes to model and handle real-life biological data using modern libraries from the R ecosystem Key FeaturesApply modern R packages to handle biological data using real-world examplesRepresent biological data with advanced visualizations suitable for research and publicationsHandle real-world problems in bioinformatics such as next-generation sequencing, metagenomics, and automating analysesBook Description Handling biological data effectively requires an in-depth knowledge of machine learning techniques and computational skills, along with an understanding of how to use tools such as edgeR and DESeq. With the R Bioinformatics Cookbook, you’ll explore all this and more, tackling common and not-so-common challenges in the bioinformatics domain using real-world examples. This book will use a recipe-based approach to show you how to perform practical research and analysis in computational biology with R. You will learn how to effectively analyze your data with the latest tools in Bioconductor, ggplot, and tidyverse. The book will guide you through the essential tools in Bioconductor to help you understand and carry out protocols in RNAseq, phylogenetics, genomics, and sequence analysis. As you progress, you will get up to speed with how machine learning techniques can be used in the bioinformatics domain. You will gradually develop key computational skills such as creating reusable workflows in R Markdown and packages for code reuse. By the end of this book, you’ll have gained a solid understanding of the most important and widely used techniques in bioinformatic analysis and the tools you need to work with real biological data. What you will learnEmploy Bioconductor to determine differential expressions in RNAseq dataRun SAMtools and develop pipelines to find single nucleotide polymorphisms (SNPs) and IndelsUse ggplot to create and annotate a range of visualizationsQuery external databases with Ensembl to find functional genomics informationExecute large-scale multiple sequence alignment with DECIPHER to perform comparative genomicsUse d3.js and Plotly to create dynamic and interactive web graphicsUse k-nearest neighbors, support vector machines and random forests to find groups and classify dataWho this book is for This book is for bioinformaticians, data analysts, researchers, and R developers who want to address intermediate-to-advanced biological and bioinformatics problems by learning through a recipe-based approach. Working knowledge of R programming language and basic knowledge of bioinformatics are prerequisites.

MacHine-Learning Based Sequence Analysis, Bioinformatics and Nanopore Transduction Detection

Stephen Winters-Hilt
MacHine Learning Based Sequence Analysis Bioinformatics and Nanopore Transduction Detection Book PDF

Author : Stephen Winters-Hilt
Publisher : Lulu.com
Page : 436 pages
File Size : 43,7 Mb
Release : 2011-05-01
Category : Computers
ISBN : 9781257645251

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MacHine-Learning Based Sequence Analysis, Bioinformatics and Nanopore Transduction Detection by Stephen Winters-Hilt Pdf

This is intended to be a simple and accessible book on machine learning methods and their application in computational genomics and nanopore transduction detection. This book has arisen from eight years of teaching one-semester courses on various machine-learning, cheminformatics, and bioinformatics topics. The book begins with a description of ad hoc signal acquisition methods and how to orient on signal processing problems with the standard tools from information theory and signal analysis. A general stochastic sequential analysis (SSA) signal processing architecture is then described that implements Hidden Markov Model (HMM) methods. Methods are then shown for classification and clustering using generalized Support Vector Machines, for use with the SSA Protocol, or independent of that approach. Optimization metaheuristics are used for tuning over algorithmic parameters throughout. Hardware implementations and short code examples of the various methods are also described.

Introduction to Machine Learning and Bioinformatics

Sushmita Mitra,Sujay Datta,Theodore Perkins,George Michailidis
Introduction to Machine Learning and Bioinformatics Book PDF

Author : Sushmita Mitra,Sujay Datta,Theodore Perkins,George Michailidis
Publisher : CRC Press
Page : 384 pages
File Size : 49,6 Mb
Release : 2008-06-05
Category : Mathematics
ISBN : 9781420011784

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Introduction to Machine Learning and Bioinformatics by Sushmita Mitra,Sujay Datta,Theodore Perkins,George Michailidis Pdf

Lucidly Integrates Current Activities Focusing on both fundamentals and recent advances, Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas relate to each other. Examines Connections between Machine Learning & Bioinformatics The book begins with a brief historical overview of the technological developments in biology. It then describes the main problems in bioinformatics and the fundamental concepts and algorithms of machine learning. After forming this foundation, the authors explore how machine learning techniques apply to bioinformatics problems, such as electron density map interpretation, biclustering, DNA sequence analysis, and tumor classification. They also include exercises at the end of some chapters and offer supplementary materials on their website. Explores How Machine Learning Techniques Can Help Solve Bioinformatics Problems Shedding light on aspects of both machine learning and bioinformatics, this text shows how the innovative tools and techniques of machine learning help extract knowledge from the deluge of information produced by today’s biological experiments.

Deep Learning in Bioinformatics

Habib Izadkhah
Deep Learning in Bioinformatics Book PDF

Author : Habib Izadkhah
Publisher : Academic Press
Page : 382 pages
File Size : 40,8 Mb
Release : 2022-01-08
Category : Science
ISBN : 9780128238363

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Deep Learning in Bioinformatics by Habib Izadkhah Pdf

Deep Learning in Bioinformatics: Techniques and Applications in Practice introduces the topic in an easy-to-understand way, exploring how it can be utilized for addressing important problems in bioinformatics, including drug discovery, de novo molecular design, sequence analysis, protein structure prediction, gene expression regulation, protein classification, biomedical image processing and diagnosis, biomolecule interaction prediction, and in systems biology. The book also presents theoretical and practical successes of deep learning in bioinformatics, pointing out problems and suggesting future research directions. Dr. Izadkhah provides valuable insights and will help researchers use deep learning techniques in their biological and bioinformatics studies. Introduces deep learning in an easy-to-understand way Presents how deep learning can be utilized for addressing some important problems in bioinformatics Presents the state-of-the-art algorithms in deep learning and bioinformatics Introduces deep learning libraries in bioinformatics

Bioinformatics for Beginners

Supratim Choudhuri
Bioinformatics for Beginners Book PDF

Author : Supratim Choudhuri
Publisher : Elsevier
Page : 238 pages
File Size : 54,7 Mb
Release : 2014-05-09
Category : Medical
ISBN : 9780124105102

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Bioinformatics for Beginners by Supratim Choudhuri Pdf

Bioinformatics for Beginners: Genes, Genomes, Molecular Evolution, Databases and Analytical Tools provides a coherent and friendly treatment of bioinformatics for any student or scientist within biology who has not routinely performed bioinformatic analysis. The book discusses the relevant principles needed to understand the theoretical underpinnings of bioinformatic analysis and demonstrates, with examples, targeted analysis using freely available web-based software and publicly available databases. Eschewing non-essential information, the work focuses on principles and hands-on analysis, also pointing to further study options. Avoids non-essential coverage, yet fully describes the field for beginners Explains the molecular basis of evolution to place bioinformatic analysis in biological context Provides useful links to the vast resource of publicly available bioinformatic databases and analysis tools Contains over 100 figures that aid in concept discovery and illustration

Deep Learning for Biomedical Data Analysis

Mourad Elloumi
Deep Learning for Biomedical Data Analysis Book PDF

Author : Mourad Elloumi
Publisher : Springer Nature
Page : 358 pages
File Size : 50,5 Mb
Release : 2021-07-13
Category : Medical
ISBN : 9783030716769

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Deep Learning for Biomedical Data Analysis by Mourad Elloumi Pdf

This book is the first overview on Deep Learning (DL) for biomedical data analysis. It surveys the most recent techniques and approaches in this field, with both a broad coverage and enough depth to be of practical use to working professionals. This book offers enough fundamental and technical information on these techniques, approaches and the related problems without overcrowding the reader's head. It presents the results of the latest investigations in the field of DL for biomedical data analysis. The techniques and approaches presented in this book deal with the most important and/or the newest topics encountered in this field. They combine fundamental theory of Artificial Intelligence (AI), Machine Learning (ML) and DL with practical applications in Biology and Medicine. Certainly, the list of topics covered in this book is not exhaustive but these topics will shed light on the implications of the presented techniques and approaches on other topics in biomedical data analysis. The book finds a balance between theoretical and practical coverage of a wide range of issues in the field of biomedical data analysis, thanks to DL. The few published books on DL for biomedical data analysis either focus on specific topics or lack technical depth. The chapters presented in this book were selected for quality and relevance. The book also presents experiments that provide qualitative and quantitative overviews in the field of biomedical data analysis. The reader will require some familiarity with AI, ML and DL and will learn about techniques and approaches that deal with the most important and/or the newest topics encountered in the field of DL for biomedical data analysis. He/she will discover both the fundamentals behind DL techniques and approaches, and their applications on biomedical data. This book can also serve as a reference book for graduate courses in Bioinformatics, AI, ML and DL. The book aims not only at professional researchers and practitioners but also graduate students, senior undergraduate students and young researchers. This book will certainly show the way to new techniques and approaches to make new discoveries.

Computational Genomics with R

Altuna Akalin
Computational Genomics with R Book PDF

Author : Altuna Akalin
Publisher : CRC Press
Page : 462 pages
File Size : 54,6 Mb
Release : 2020-12-16
Category : Mathematics
ISBN : 9781498781862

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Computational Genomics with R by Altuna Akalin Pdf

Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.